System and method for sparse gaussian process regression using predictive measures

a process regression and predictive measure technology, applied in the field of computer systems, can solve problems such as the stoppage of the incremental addition of basis vectors, and achieve the effect of improving the predictive performance of the model

Inactive Publication Date: 2009-06-11
OATH INC
View PDF0 Cites 56 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The iterative addition of basis vectors may stop when predictive performance of the model degrades or no significant performance improvement is seen.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • System and method for sparse gaussian process regression using predictive measures
  • System and method for sparse gaussian process regression using predictive measures
  • System and method for sparse gaussian process regression using predictive measures

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

Exemplary Operating Environment

[0016]FIG. 1 illustrates suitable components in an exemplary embodiment of a general purpose computing system. The exemplary embodiment is only one example of suitable components and is not intended to suggest any limitation as to the scope of use or functionality of the invention. Neither should the configuration of components be interpreted as having any dependency or requirement relating to any one or combination of components illustrated in the exemplary embodiment of a computer system. The invention may be operational with numerous other general purpose or special purpose computing system environments or configurations.

[0017]The invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, and so forth, which perform particular tasks or implement particular abstract data types....

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

An improved system and method is provided for sparse Gaussian process regression using predictive measures. A Gaussian process regressor model may be construction by interleaving basis vector set selection and hyper-parameter optimization until the chosen predictive measure stabilizes. One of various LOO-CV based predictive measures may be used to find an optimal set of active basis vectors for building a sparse Gaussian process regression model by sequentially adding basis vectors selected using a chosen predictive measure. In a given iteration, a predictive measure is computed for each of the basis vectors in a candidate set of basis vectors and the basis vector with the best predictive measure is selected. The iterative addition of basis vectors may stop when predictive performance of the model degrades or no significant performance improvement is seen.

Description

FIELD OF THE INVENTION[0001]The invention relates generally to computer systems, and more particularly to an improved system and method for sparse Gaussian process regression using predictive measures.BACKGROUND OF THE INVENTION[0002]Gaussian process (GP) regression models are flexible, powerful, and easy to implement probabilistic models that can be used to solve regression problems in many areas of application. See for example C. E. Rasmussen and C. K. I. Williams, Gaussian Processes for Machine Learning, The MIT Press, 2006. For instance, regression problems may arise in applications such as time series prediction of web pages, learning of search page relevance as a function of properties of query and result pages, click through rate prediction, and so forth. While GPs exhibit state of the art performance as a probabilistic tool for regression, they are not used in applications that have large training sets because training time becomes a bottleneck. In particular, GPs suffer fro...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(United States)
IPC IPC(8): G06N7/00
CPCG06N7/005G06N7/01
Inventor SELLAMANICKAM, SUNDARARAJANSELVARAJ, SATHIYA KEERTHI
Owner OATH INC
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap